c21 opened a new pull request #34270:
URL: https://github.com/apache/spark/pull/34270
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### What changes were proposed in this pull request?
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This PR is to disable two level of maps for final hash aggregation by
default. The feature was introduced in
https://github.com/apache/spark/pull/32242 and we found it can lead to query
performance regression when the final aggregation gets rows with a lot of
distinct keys. The 1st level hash map is full so a lot of rows will waste the
1st hash map lookup and inserted into 2nd hash map. This feature still benefits
query with not so many distinct keys though, so introducing a config here
`spark.sql.codegen.aggregate.final.map.twolevel.enabled`, to allow query to
enable the feature when seeing benefit.
### Why are the changes needed?
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Fix query regression.
### Does this PR introduce _any_ user-facing change?
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Yes, the introduced `spark.sql.codegen.aggregate.final.map.twolevel.enabled`
config.
### How was this patch tested?
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Existing unit test in `AggregationQuerySuite.scala`.
Also verified generated code for an example query in the file:
```
spark.sql(
"""
|SELECT key, avg(value)
|FROM agg1
|GROUP BY key
""".stripMargin)
```
Verified the generated code for final hash aggregation not have two level
maps by default:
https://gist.github.com/c21/d4ce87ef28a22d1ce839e0cda000ce14 .
Verified the generated code for final hash aggregation have two level maps
if enabling the config:
https://gist.github.com/c21/4b59752c1f3f98303b60ccff66b5db69 .
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